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Psychonomic Bulletin & Review

, Volume 25, Issue 2, pp 696–703 | Cite as

A hard-to-read font reduces the framing effect in a large sample

  • Christoph W. Korn
  • Juliane Ries
  • Lennart Schalk
  • Yulia Oganian
  • Henrik Saalbach
Brief Report

Abstract

How can apparent decision biases, such as the framing effect, be reduced? Intriguing findings within recent years indicate that foreign language settings reduce framing effects, which has been explained in terms of deeper cognitive processing. Because hard-to-read fonts have been argued to trigger deeper cognitive processing, so-called cognitive disfluency, we tested whether hard-to-read fonts reduce framing effects. We found no reliable evidence for an effect of hard-to-read fonts on four framing scenarios in a laboratory (final N = 158) and an online study (N = 271). However, in a preregistered online study with a rather large sample (N = 732), a hard-to-read font reduced the framing effect in the classic “Asian disease” scenario (in a one-sided test). This suggests that hard-read-fonts can modulate decision biases—albeit with rather small effect sizes. Overall, our findings stress the importance of large samples for the reliability and replicability of modulations of decision biases.

Keywords

Decision-making biases Apparent irrationalities Cognition Syllogistic reasoning 

Notes

Acknowledgments

The authors thank Alica Thissen and Christian Hahn for their help with data collection and discussion. They thank Dr. Dominik Leiner, the administrator of SoSci Survey, without whom Experiment 3 would not have been possible. Funding was provided by a research grant from Saarland University. CWK was supported by the SFB TRR 169 during the final stages of manuscript preparation. The funders had no role in the study.

Compliance with ethical standards

Declaration of interest

No conflict of interest.

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Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  • Christoph W. Korn
    • 1
  • Juliane Ries
    • 2
  • Lennart Schalk
    • 3
    • 4
  • Yulia Oganian
    • 5
  • Henrik Saalbach
    • 6
  1. 1.Institute for Systems NeuroscienceUniversity Medical Center Hamburg-EppendorfHamburgGermany
  2. 2.Saarland UniversitySaarbrückenGermany
  3. 3.ETH ZurichZurichSwitzerland
  4. 4.PH SchwyzGoldauSwitzerland
  5. 5.School of MedicineUniversity of California San FranciscoSan FranciscoUSA
  6. 6.Leipzig UniversityLeipzigGermany

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